Curious about quantum computing and how it might be applied in biological research across different areas and scales? Check out this Comment from scientists with diverse backgrounds on the basic principles of quantum computing.
https://t.co/UiIrjZLDE0
https://t.co/UiIrjZLDE0
Artificial Intelligence may beat us in chess, but not in memory.
Out now in PhysRevLett
https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.126.018301
Out now in PhysRevLett
https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.126.018301
یک کلاس آمار جذاب از Richard McElreath.
ایشون رئیس مرکز انسانشناسی ماکس پلانکه.
Max Planck Institute for Evolutionary Anthropology
ویدیوها در یوتیوب و در آپارات:
🎞 https://www.aparat.com/playlist/765182
ایشون رئیس مرکز انسانشناسی ماکس پلانکه.
Max Planck Institute for Evolutionary Anthropology
ویدیوها در یوتیوب و در آپارات:
🎞 https://www.aparat.com/playlist/765182
Wikipedia
Richard McElreath
American anthropologist
One important addition to the discussion on networks
"True scale-free networks hidden by finite size effects"
https://t.co/QSi0W4KGyo
"True scale-free networks hidden by finite size effects"
https://t.co/QSi0W4KGyo
💰 36 fully funded (four years of tuition fee + an annual stipend of €18,500) structured #PhD positions in
Foundations of Data Science
in the only English speaking country of the EU (apart from Malta!)
Application deadline: 5 February
https://t.co/EAEoYtOidj
Foundations of Data Science
in the only English speaking country of the EU (apart from Malta!)
Application deadline: 5 February
https://t.co/EAEoYtOidj
💰 The ICT department is opening several #PhD and #PostDoc positions, see https://t.co/pt85Qt3GhF
This is not the US! Take a look:https://t.co/TBWhbE6Mzw
This is not the US! Take a look:https://t.co/TBWhbE6Mzw
Combinatorial approach to spreading processes on networks
Dario Mazzilli, Filippo Radicchi
https://arxiv.org/pdf/2101.02176
Stochastic spreading models defined on complex network topologies are used to mimic the diffusion of diseases, information, and opinions in real-world systems. Existing theoretical approaches to the characterization of the models in terms of microscopic configurations rely on some approximation of independence among dynamical variables, thus introducing a systematic bias in the prediction of the ground-truth dynamics. Here, we develop a combinatorial framework based on the approximation that spreading may occur only along the shortest paths connecting pairs of nodes. The approximation overestimates dynamical correlations among node states and leads to biased predictions. Systematic bias is, however, pointing in the opposite direction of existing approximations. We show that the combination of the two biased approaches generates predictions of the ground-truth dynamics that are more accurate than the ones given by the two approximations if used in isolation. We further take advantage of the combinatorial approximation to characterize theoretical properties of some inference problems, and show that the reconstruction of microscopic configurations is very sensitive to both the place where and the time when partial knowledge of the system is acquired.
Dario Mazzilli, Filippo Radicchi
https://arxiv.org/pdf/2101.02176
Stochastic spreading models defined on complex network topologies are used to mimic the diffusion of diseases, information, and opinions in real-world systems. Existing theoretical approaches to the characterization of the models in terms of microscopic configurations rely on some approximation of independence among dynamical variables, thus introducing a systematic bias in the prediction of the ground-truth dynamics. Here, we develop a combinatorial framework based on the approximation that spreading may occur only along the shortest paths connecting pairs of nodes. The approximation overestimates dynamical correlations among node states and leads to biased predictions. Systematic bias is, however, pointing in the opposite direction of existing approximations. We show that the combination of the two biased approaches generates predictions of the ground-truth dynamics that are more accurate than the ones given by the two approximations if used in isolation. We further take advantage of the combinatorial approximation to characterize theoretical properties of some inference problems, and show that the reconstruction of microscopic configurations is very sensitive to both the place where and the time when partial knowledge of the system is acquired.
Exciting news! We are announcing a new undergraduate program in Quantitative Social Sciences at @dnds_ceu.
https://t.co/O5TOfjQ0ra
Our program combines rigorous ("hard sciences"-level) mathematics, statistics, and programming with the pillars of the social sciences.
The multidisciplinary program is designed to form a next generation of researchers able to make sense of the huge volume of data on human behavior, while based fully on the epistemological foundations of the social sciences (Sociology, Economics, Environ. Sci., Pol. Sci.)
We will be offering a limited number of 🚨full scholarships🚨, covering full tuition waiver and housing aid.
The program is hosted by @dnds_ceu at @ceu, in Vienna 🇦🇹, often ranked the most livable city in the world.
Deadlines: Feb. 1, Apr. 12, 2021
https://undergraduate.ceu.edu/qss/about
https://t.co/O5TOfjQ0ra
Our program combines rigorous ("hard sciences"-level) mathematics, statistics, and programming with the pillars of the social sciences.
The multidisciplinary program is designed to form a next generation of researchers able to make sense of the huge volume of data on human behavior, while based fully on the epistemological foundations of the social sciences (Sociology, Economics, Environ. Sci., Pol. Sci.)
We will be offering a limited number of 🚨full scholarships🚨, covering full tuition waiver and housing aid.
The program is hosted by @dnds_ceu at @ceu, in Vienna 🇦🇹, often ranked the most livable city in the world.
Deadlines: Feb. 1, Apr. 12, 2021
https://undergraduate.ceu.edu/qss/about
CEU Undergraduate
About QSS
The BA in Quantitative Social Sciences combines the study of human societies with a rigorous foundation in mathematics, statistics, computation and data science.
اثر ویتامین D بر بیماری کرونا:
“All the observational studies show strong vitamin D effects on infectiousness, morbidity and mortality,” Davis says. [..] All of this evidence together, he says, makes it “very, very plain that vitamin D has a material effect”. https://t.co/oVKoGpF7sD
“All the observational studies show strong vitamin D effects on infectiousness, morbidity and mortality,” Davis says. [..] All of this evidence together, he says, makes it “very, very plain that vitamin D has a material effect”. https://t.co/oVKoGpF7sD
the Guardian
Does vitamin D combat Covid?
It’s cheap, widely available and might help us fend off the virus. So should we all be dosing up on the sunshine nutrient?
'Noise' is everything in an image that isn’t real signal, and no image is completely free of it.
https://t.co/jiUiHTkLOu
https://t.co/jiUiHTkLOu
Nature
Sharper signals: how machine learning is cleaning up microscopy images
Computers trained to reduce the noise in micrographs can now tackle fresh data by themselves.
💰 Interested in studying brain computations using functional imaging, behavior, physiology, applied mathematics and #zebrafish, at @KISNeuro, @NTNUnorway, on a project funded by @forskningsradet ? We are hiring, join us ! https://t.co/cHQHXiQVBF
💰 New #postdoc position to develop novel models of large-scale brain dynamics, and use these to uncover brain activity causing OCD
https://t.co/TxtwlHYVyt
https://t.co/TxtwlHYVyt
A thread on a working paper ‘Why U.S. Immigration Barriers Matter for the Global Advancement of Science’
https://t.co/XnuwTQGkcz
https://t.co/XnuwTQGkcz
💉 Is it a good idea to delay the second jab? "We should stick with what’s been proven to work. We don’t want to be creative for some unclear benefit and then have an unexpected problem."
https://t.co/9Aan3D0aW7
https://t.co/9Aan3D0aW7
Nature
How can countries stretch COVID vaccine supplies? Scientists are divided over dosing strategies
Researchers worry that efforts to free up limited vaccine doses are driven by desperation rather than data.
INHOMOGENEOUS RANDOM SYSTEMS
26-27 January 2021 Online
http://irs.math.cnrs.fr/2021/
The aim of this annual workshop is to bring together mathematicians and physicists working on disordered or random systems, and to discuss recent developments on themes of common interest. Each day is devoted to a specific topic.
Tuesday 26 January:
Structure and function of complex networks: epidemics and optimization. Titles and abstracts
Wednesday 27 January:
Statistical Physics of Active Matter. Titles and abstracts
The conference and online participation are free and open to all. To receive your connection link, please register in advance by sending an e-mail with your name and affiliation to:
26-27 January 2021 Online
http://irs.math.cnrs.fr/2021/
The aim of this annual workshop is to bring together mathematicians and physicists working on disordered or random systems, and to discuss recent developments on themes of common interest. Each day is devoted to a specific topic.
Tuesday 26 January:
Structure and function of complex networks: epidemics and optimization. Titles and abstracts
Wednesday 27 January:
Statistical Physics of Active Matter. Titles and abstracts
The conference and online participation are free and open to all. To receive your connection link, please register in advance by sending an e-mail with your name and affiliation to:
inter@math.cnrs.fr with subject: IRS 2021Random minimum spanning trees
Christina Goldschmidt from the Department of Statistics in Oxford talks about her joint work with Louigi Addario-Berry (McGill), Nicolas Broutin (Paris Sorbonne University) and Gregory Miermont (ENS Lyon) on random minimum spanning trees.
https://www.maths.ox.ac.uk/node/30217
Christina Goldschmidt from the Department of Statistics in Oxford talks about her joint work with Louigi Addario-Berry (McGill), Nicolas Broutin (Paris Sorbonne University) and Gregory Miermont (ENS Lyon) on random minimum spanning trees.
https://www.maths.ox.ac.uk/node/30217
💉 Can you spread Covid-19 if you get the vaccine?
The reason we don’t know if the vaccine can prevent transmission is twofold. One reason is practical. The first order of business for vaccines is preventing exposed individuals from getting sick, so that’s what the clinical trials for Covid-19 shots were designed to determine. We simply don’t have public health data to answer the question of transmission yet.
The second reason is immunological. From a scientific perspective, there are a lot of complex questions about how the vaccine generates antibodies in the body that haven’t yet been studied. Scientists are still eager to explore these immunological rabbit holes, but it could take years to reach the bottom of them.
To prevent Covid-19 transmission, another type of antibodies could be the more important player. The immune system that patrols your outward-facing mucosal surfaces—spaces like the nose, the throat, the lungs, and digestive tract—relies on immunoglobulin A, or IgA antibodies. And we don’t yet know how well existing vaccines incite IgA antibodies.
People who get sick and recover from Covid-19 produce a ton of these more-specialized IgA antibodies. Because IgA antibodies occupy the same respiratory tract surfaces involved in transmitting SARS-CoV-2, we could reasonably expect that people who recover from Covid-19 aren’t spreading the virus any more. (Granted, this may also depend on how much of the virus that person was exposed to.)
But we don’t know if people who have IgG antibodies from the vaccine are stopping the virus in our respiratory tracts in the same way. And even if we did, scientists still don’t know how much of the SARS-CoV-2 virus it takes to cause a new infection. So even if we understood how well a vaccine worked to prevent a virus from replicating along the upper respiratory tract, it’d be extremely difficult to tell if that would mean a person couldn’t transmit the disease.
The reason we don’t know if the vaccine can prevent transmission is twofold. One reason is practical. The first order of business for vaccines is preventing exposed individuals from getting sick, so that’s what the clinical trials for Covid-19 shots were designed to determine. We simply don’t have public health data to answer the question of transmission yet.
The second reason is immunological. From a scientific perspective, there are a lot of complex questions about how the vaccine generates antibodies in the body that haven’t yet been studied. Scientists are still eager to explore these immunological rabbit holes, but it could take years to reach the bottom of them.
To prevent Covid-19 transmission, another type of antibodies could be the more important player. The immune system that patrols your outward-facing mucosal surfaces—spaces like the nose, the throat, the lungs, and digestive tract—relies on immunoglobulin A, or IgA antibodies. And we don’t yet know how well existing vaccines incite IgA antibodies.
People who get sick and recover from Covid-19 produce a ton of these more-specialized IgA antibodies. Because IgA antibodies occupy the same respiratory tract surfaces involved in transmitting SARS-CoV-2, we could reasonably expect that people who recover from Covid-19 aren’t spreading the virus any more. (Granted, this may also depend on how much of the virus that person was exposed to.)
But we don’t know if people who have IgG antibodies from the vaccine are stopping the virus in our respiratory tracts in the same way. And even if we did, scientists still don’t know how much of the SARS-CoV-2 virus it takes to cause a new infection. So even if we understood how well a vaccine worked to prevent a virus from replicating along the upper respiratory tract, it’d be extremely difficult to tell if that would mean a person couldn’t transmit the disease.
Quartz
Can you spread Covid-19 if you get the vaccine?
Answering this question will take us one step closer to our new normal.